Dataset Information

Structural similarity of genetically interacting proteins.

ABSTRACT: The study of gene mutants and their interactions is fundamental to understanding gene function and backup mechanisms within the cell. The recent availability of large scale genetic interaction networks in yeast and worm allows the investigation of the biological mechanisms underlying these interactions at a global scale. To date, less than 2% of the known genetic interactions in yeast or worm can be accounted for by sequence similarity.Here, we perform a genome-scale structural comparison among protein pairs in the two species. We show that significant fractions of genetic interactions involve structurally similar proteins, spanning 7-10% and 14% of all known interactions in yeast and worm, respectively. We identify several structural features that are predictive of genetic interactions and show their superiority over sequence-based features.Structural similarity is an important property that can explain and predict genetic interactions. According to the available data, the most abundant mechanism for genetic interactions among structurally similar proteins is a common interacting partner shared by two genetically interacting proteins.

SUBMITTER: Dror O

PROVIDER: S-EPMC2525628 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Structural similarity of genetically interacting proteins.

Dror Oranit O Schneidman-Duhovny Dina D Shulman-Peleg Alexandra A Nussinov Ruth R Wolfson Haim J HJ Sharan Roded R

BMC systems biology 20080731

<h4>Background</h4>The study of gene mutants and their interactions is fundamental to understanding gene function and backup mechanisms within the cell. The recent availability of large scale genetic interaction networks in yeast and worm allows the investigation of the biological mechanisms underlying these interactions at a global scale. To date, less than 2% of the known genetic interactions in yeast or worm can be accounted for by sequence similarity.<h4>Results</h4>Here, we perform a genome ...[more]

PMID: 18671848

Similar Datasets

Project description:Association mapping of factors that condition pyrethroid resistance in Aedes aegypti has consistently identified genes in multiple functional groups. Toward better understanding of the mechanisms involved, we examined high throughput sequencing data (HTS) from two Aedes aegypti aegypti collections from Merida, Yucatan, Mexico treated with either permethrin or deltamethrin. Exome capture enrichment for coding regions and the AaegL5 annotation were used to identify genes statistically associated with resistance. The frequencies of single nucleotide polymorphisms (SNPs) were compared between resistant and susceptible mosquito pools using a contingency ?2 analysis. The -log10(?2 p value) was calculated at each SNP site, with a weighted average determined from all sites in each gene. Genes with -log10(?2 p value) ? 4.0 and present among all 3 treatment groups were subjected to gene set enrichment analysis (GSEA). We found that several functional groups were enriched compared to all coding genes. These categories were transport, signal transduction and metabolism, in order from highest to lowest statistical significance. Strikingly, 21 genes with demonstrated association to synaptic function were identified. In the high association group (n = 1,053 genes), several genes were identified that also genetically or physically interact with the voltage-gated sodium channel (VGSC). These genes were eg., CHARLATAN (CHL), a transcriptional regulator, several ankyrin-domain proteins, PUMILIO (PUM), a translational repressor, and NEDD4 (E3 ubiquitin-protein ligase). There were 13 genes that ranked among the top 10%: these included VGSC; CINGULIN, a predicted neuronal gap junction protein, and the aedine ortholog of NERVY (NVY), a transcriptional regulator. Silencing of CHL and NVY followed by standard permethrin bottle bioassays validated their association with permethrin resistance. Importantly, VGSC levels were also reduced about 50% in chl- or nvy-dsRNA treated mosquitoes. These results are consistent with the contribution of a variety of neuronal pathways to pyrethroid resistance in Ae. aegypti.

Project description:The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels), each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD) of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good agreement with the consensus model of the resting state VSD and the spin-spin distance histograms from ESR/DEER experiments on T4 lysozyme are accurately reproduced.

Dataset Information

Structural similarity of genetically interacting proteins.

Publications

Structural similarity of genetically interacting proteins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets